Is This Your Final Destination? Created Steppingstone Paths Differ Depending on Whether Paths Terminate or Continue

Abstract

In the ecological approach to perceiving and acting, affordances are emergent, higher-order relationships between animals and their environment. Accordingly, studies have shown that affordances are perceived ‘as such’ rather than as combinations of lower-order constituents of that affordance. We investigated whether affordances are created in the same way. Participants used circular rubber mats to create steppingstone paths from Mat A to Mat B (in the ‘Stop-at-B’ condition) and from Mat A to Mat B to Mat C (in the ‘Continue-to-C’ condition). We derived and analyzed sets of variables related to gap distance, path trajectory, and path variability. Consistent with our hypotheses, participants configured the A-to-B portion of the path differently in each condition—in particular, with respect to variables related to gap distance and path variability. Conversely, when participants configured paths from A-to-B-to-C, we found no evidence that they configured the A-to-B portion of the path differently than the B-to-C portion of the path. Overall, the results suggest that affordances for crossing a path from A-to-B were created distinctly from those for crossing a path from A-to-B-to-C. More generally, they suggest that affordances were created as emergent higher-order relationships rather than as a combination of lower-order constituents.

Introduction

People exhibit remarkable sensitivity to affordances—opportunities for behavior emerging from higher-order relations between themselves and the environment under a given set of dynamically unfolding circumstances (Gibson, 1979/2015). For example, people can perceive affordances for behaviors such as passing through an aperture or reaching for an object across many different sets of circumstances (Carello et al., 1989; Franchak et al., 2012; Walsh et al., 2024; Warren & Whang, 1987). In the ecological approach to perceiving and acting, it is proposed that these higher-order relations between animal and environment lawfully structure stimulation patterns such that the structure in these stimulation patterns provides information about such relations (Blau & Wagman, 2023; Turvey, 2019). Therefore, in the ecological approach to perceiving and acting, it is proposed that people (and other animals) directly perceive affordances for a given behavior by detecting lawfully structured information about such affordances without any need to combine separate perceptions of lower-order constituents of that affordance—including properties of the animal, as such, or the environment, as such. For example, it is proposed that people can perceive affordances for reaching an object by detecting the lawfully structured stimulation patterns that provide information about affordances for reaching the object, without independently perceiving and comparing arm length and object distance. In other words, in the ecological approach, a given affordance ought to be perceived ‘as such’ or, equivalently, as a ‘complex particular’—an emergent higher-order relationship rather than as a combination of perceived lower-order constituent properties of that affordance (Turvey, 2015; Wagman & Stoffregen, 2020).

Support for this hypothesis has been found by studies that have investigated perception of many different affordances across many different sets of circumstances. For example, affordances for passing through an aperture are perceived as an emergent higher-order relation between animal and environment under dynamically unfolding circumstances and not merely as a comparison of aperture width and shoulder width (Franchak et al., 2012; Warren & Whang, 1987). Support for this hypothesis has also been found by such studies even when the lower-order constituent properties of the perceived affordance include other (lower-order) affordances. For example, studies have shown that affordances for reaching-with-an-arm-plus-tool are perceived as an emergent higher-order relation and not merely as an additive combination of perceived affordances for reaching with the arm and perceived affordances for reaching with the tool (Thomas & Riley, 2014; Wagman & Stoffregen, 2020; see Bongers, et al., 2004). Similarly, studies have shown that affordances for reaching-while-jumping are perceived as an emergent higher-order relation and not as a combination of affordances-for-reaching and affordances-for-jumping (Thomas et al., 2018).

In addition to perceiving affordances, people are also capable of creating affordances. That is, people can reconfigure or alter relations between themselves and the environment to bring a particular affordance into existence. In such tasks, rather than being asked to merely choose a behavior from among many possible alternatives, participants are asked to choose a behavior from among many possible alternatives that generates new opportunities for behavior. For example, people can assemble or configure components of a hand-held implement such that the completed or reconfigured implement affords use in a particular tool use task (Mangalam et al., 2019; Wagman et al., 2016a, 2016b). Likewise, they can use a hand-held implement to reconfigure or alter the affordances of a struck object or surface, such as in skilled stone knapping (Nonaka et al., 2010). More germane to this study, people can arrange a configuration of steppingstones (or mats) to create affordances for traversing a particular surface (Jeschke, et al., 2020). Moreover, they create different configurations of steppingstones (or mats) to cross a surface under different task constraints (i.e., under different sets of dynamically unfolding circumstances, Wagman et al., 2024). For example, Wagman et al (2024) found that participants created different path configurations depending on how that path was to be used—that is, whether the to-be-created path was to be crossed quickly or carefully or whether it was to be easy or fun to use.

The Present Study

In this study, we use the paradigm established by Jeschke et al. (2020) and further developed by Wagman et al (2024) to investigate the novel hypothesis that affordances—in this case, affordances for traversing surface—are created as a complex particular. Given that previous research has provided evidence that affordances can be perceived as emergent higher-order relationships rather than as a combination of perceived lower-order constituent components of those affordances, it is possible (perhaps likely) that affordances are created in the same way. That is, it is possible that affordances are created ‘as such’—as a ‘complex particular’—and not merely as combination of the lower-order constituents of that affordance.

To investigate this novel hypothesis, we asked whether participants would create different path configurations for traversing a surface from location A to location B depending on whether their created path terminated at location B, or continued from location B to location C. When the created path terminated at B, affordances for traversing the path from A-to-B existed in and of themselves and not as necessary constituent components of a higher-order affordance for traversing any other part of the surface. However, when the path continued to C, affordances for traversing the path from A-to-B existed in and of themselves and also as necessary (lower-order) constituent components of (higher-order) affordances for traversing the longer path from A-to-B-to-C. That is, when the path continued to C, the A-to-B portion of the path would afford crossing not only on its own but also in relation to traversing the longer path from A-to-B-to-C (cf. Jansen & Fajen, 2024).

In each condition, we compared the configurations of the A-to-B portions of the paths created with respect to sets of dependent measures related to distance, trajectory, and variability (see below for detail; cf. Wagman et al. 2024). If affordances are created ‘as such’ or as ‘complex particulars’—and not merely as combination of lower-order constituents of that affordance—then the path from A-to-B should be created ‘as such’ when the path terminated at B but not when the path continued to location C. Therefore, we expected that participants would create different path configurations from A-to-B in each condition.

When the path terminates at B, the A-to-B portion is an end-in-itself. However, when the path terminates at location C, the A-to-B portion of the task is merely a means-to-an-end. Consequently, the task constraints of configuring the A-to-B portion of the path emphasize expediency to a greater degree when the path continues to C than when it terminates at B. In previous research, Wagman et al. (2024) found that when task constraints emphasized expediency, participants configured paths using fewer mats and with smaller variability in mat placement. Therefore, in the present study, we expected a similar pattern of results. That is, we expected that differences in the configurations of the A-to-B portions of paths would emerge with respect to variables related to distance and variability and not necessarily with respect to variables related to trajectory. In particular, we expected that participants would configure the A-to-B portion of the path with fewer mats and with less variability in mat placement when the path continued to C than when it terminated at B.

In the Continue-to-C condition, we also compared the configurations of the A-to-B and B-to-C portions of the paths with respect to the same set of dependent measures. If affordances are created ‘as such’ or, equivalently, as a ‘complex particular’—and not merely created as combination of lower-order constituents of that affordance—then the entire path from A-to-B-to-C ought to be created ‘as such’. Consequently, the task constraints of configuring the A-to-B portion of the path ought not to differ from those for configuring the B-to-C portion of the path. Both portions of the path—from A-to-B and from B-to-C—are a means-to-an-end, and neither portion of the path is an end-in-itself. In other words, in the Continue-to-C condition, the entire path—from A-to-B-to-C—is the end-in-itself. Therefore, in the Continue to C condition, we did not expect to find differences in path configuration from A-to-B and B-to-C with respect to any of the three sets of dependent measures.

This pattern of results would provide support for the novel hypothesis that the affordances for crossing a path from A-to-B are created distinctly from those for crossing a path from A-to-B-to-C as well as preliminary support for the more general hypothesis that affordances are created as a complex particular.

Method

Participants

We conducted an a priori power analysis using the G*Power program (Faul et al., 2007). Assuming a medium effect size (f = 0.25), G*Power suggested that a sample size of approximately 23 participants would be sufficient to achieve power of 0.80, given the experimental manipulations and expected patterns of results. Consequently, 25 undergraduate students were recruited from a pool of Illinois State University psychology students (cf. Jeschke, et al., 2020; Wagman et al., 2024). Participants had a mean standing height of 174.5 cm (SD = 10.7 cm), a mean leg length of 87.9 cm (SD = 7.5 cm), and a mean maximum stepping distance of 95.0 cm (SD = 19.3 cm; see below for measurement details). We did not collect demographic data on age or gender of participants. Each participant provided written consent prior to participation and received course credit in exchange for their participation. The study protocol was approved by the Institutional Review Board and conducted in accordance with the Declaration of Helsinki.

Materials and Apparatus

The experiment was conducted in a 630 cm long × 220 cm wide section of a hallway inside a classroom building on the Illinois State University campus (see Figure 1; cf. Wagman et al., 2024). Participants created stepping paths by placing circular orange rubber mats (25.4 cm in diameter, negligible thickness) one at a time on the floor. For participant safety, rubberized antislip tape was affixed to the bottom of each mat.

Figure 1.

The experimental set up. Participants were asked to use circular orange mats to create paths that would enable them to traverse the surface from Mat A and Mat B (in the Stop-at-B condition, left) and from Mat A to Mat B to Mat C (in the Continue-to-C condition, right).

Two or three additional mats (also with antislip tape affixed to the bottom) served as landmark mats, depending on condition. A tape measure was used to measure the location of each mat relative to the starting mat (marked ‘A’, see below for details, see Figure 1, left).

Procedure

One of the landmark mats (marked ‘A’) was placed on the near boundary of the surface, centered between the outer edges of the hallway. A second landmark mat (marked ‘B’) was placed halfway between the near boundary and the far boundary (i.e., 115 cm from each boundary) centered between the outer edges of the hallway (i.e., 110 cm from each wall of the hallway; see Figure 1, left).

The experiment consisted of two within-participant conditions—the ‘Stop-at-B’ condition in which participants used the additional mats to make a path from Mat A to Mat B (See Figure 1, left) and the ‘Continue-to-C’ condition in which they did so from Mat A to Mat B to Mat C (see Figure 1, right).

In the Stop-at-B condition, the participant stood on Mat A and was handed the stack of twelve additional circular orange mats. The participant was asked to make a stepping path using these mats that would enable them to traverse the surface from Mat A and Mat B under the following set of conditions: (a) mats must be stepped on in sequence, (b) only one foot could be on any mat at any given time, and (c) as much as possible, no part of any foot should touch the hallway floor. The specific instructions given to participants were as follows: ‘Your job is to make a path that goes from Mat A to Mat B. You can step on the floor when making the path but not when using the path to cross the surface. You can use as many mats as you would like to make the path’. No specific instructions were provided on how exactly the participant was to stop on Mat B.

Participants were free to use as many or as few of the mats as they liked from the stack to create the path. They could place the mats anywhere between Mat A and the destination mat (in this case, Mat B), so long as each subsequent mat was closer to the destination mat than it was to Mat A. They were free to move anywhere in the 630 cm long × 220 cm section of hallway while configuring the path. They were not required to use the path (or any part of it) while they were in the process of configuring the path, though they were not prevented from doing so either. There was no time limit on path configuration.

In the Continue-to-C condition, a third landmark mat (marked ‘C’) was placed along the far boundary centered between the two yellow cones (i.e., 110 cm from each wall of the hallway, see Figure 1, right). In this condition, the participant was handed the same stack of twelve additional circular orange mats and was asked to make a stepping path using these mats that would enable them to traverse the surface from Mat A to Mat B to Mat C under the same set of conditions as described above. The specific instructions to participants were identical to those in the ‘Stop-at-B’ condition except that ‘Mat A to Mat B’ was replaced with ‘Mat A to Mat B and then to Mat C’. No specific instructions were provided on how exactly the participant was to stop on Mat C.

Given that participants were not required to use the path while configuring it, participants were asked to return to Mat A after configuring a path in a given condition (‘Stop-at-B’ or ‘Continue-to-C’). They were then asked to use the path to traverse the surface (from Mat A to Mat B or from Mat A to Mat B to Mat C, depending on condition). While doing so, they were permitted to adjust the positioning of the mats until they were satisfied with the path layout in that condition. ¹ Participants were then escorted away from this section of the hallway.

Experimenters then measured and recorded the locations of each mat placed by the participant—specifically, the x and y coordinates of the geometric center of each mat relative to an origin located at the geometric center of Mat A (see Figure 2). The experimenters then collected the mats that had been placed by the participant. There was one trial per condition (Stop at B and Continue to C), with condition order counterbalanced between participants. ²

Figure 2.

The dependent measures included (1) the total number of mats placed by the participant (M_n); (2) the linear distance (D) between consecutive mats; (3) the ratio between D and participant’s actual maximum stepping distance (Challenge_Actual); and (4) the ratio between D and participant’s perceived maximum stepping distance (Challenge_Perceived); (5) the absolute angular distance between the geometric centers of consecutive mats (α); (6) the maximum path width (W_max), (7) the total path length (L_total); (8) the absolute change in the linear distance between the geometric centers of consecutive mats (ΔD); and (9) the absolute change in angular distance between consecutive mats (Δα) [adapted from Wagman, et al., 2024].

After the participant completed both conditions, the experimenters measured the participant’s standing height (linear distance from the ground to the top of the head while standing on the ground) and sitting height (linear distance from the ground to the top of the head while sitting on the ground with their legs extended in front of them). The difference between these values was recorded as the participant’s leg length. ³

Then the experimenters measured the participant’s perceived and actual maximum stepping distance. The participant stood on Mat A and used a laser pointer to indicate where the experimenter should place a mat such that it was at the farthest distance that the participant would be able to step with one foot, without lifting the other foot from Mat A. Once the mat was placed in this location, the participant was permitted to further instruct the experimenter on how to adjust the distance of the mat, if necessary. The experimenter then measured the linear distance between the geometric center of Mat A and the near edge of the placed mat (the participant’s perceived maximum stepping distance). The participant was then asked to turn around to face the opposite direction and to step as far as they could with one foot, without lifting the other foot from Mat A. The experimenters measured the linear distance between the toes of the trail foot and the heel of the stepping foot (the participant’s actual maximum stepping distance).

Dependent Measures

Using the x and y coordinates of the geometric center of each mat relative to that of an origin (0,0) located at the geometric center of Mat A, we derived and analyzed sets of variables related to gap distance, path trajectory, and path variability (cf. Jeschke et al., 2020; Wagman et al., 2024; Figure 2). In particular, we derived and analyzed the same set of variables as analyzed by Wagman et al. (2024).

The set of measures related to distance included (a) the total number of mats placed by the participant when creating the paths (M_n); (b) the linear distance (D) between the geometric centers of consecutive mats (starting from either Mat A or Mat B); (c) Challenge_Actual: the ratio between the mean linear distance between the geometric centers of consecutive mats (i.e., D) and participant’s actual maximum stepping distance; and (d) Challenge_Perceived: the ratio between the mean linear distance between the geometric centers of consecutive mats and participant’s perceived maximum stepping distance (see Figure 2). ⁴

The set of measures related to trajectory included (e) the absolute angular distance (α) between the geometric centers of consecutive mats (the angle between a line passing through the geometric center of each mat and a line passing through the geometric center of the first mat and parallel to the hallway walls, thus providing a finer-grained measure of path width, see Figure 2); (f) the maximum path width (W_max, i.e., the absolute distance between the largest and smallest x coordinate values, thus providing a coarser-grained measure of changes in path width; and (g) total path length (L_total)—the sum of the linear distances between the geometric centers of consecutive mats (i.e., from a given landmark mat to the last mat placed by the participant prior to the Mat B or Mat C, see Figure 2).

The set of measures related to variability included (h) the absolute change in the linear distance (ΔD) between the geometric centers of consecutive mats; and (i) the absolute change in angular distance (Δα) between consecutive mats (see Figure 2).

Results

Comparison of A-to-B Portions Paths Across the Stop-at-B and Continue-to-C Conditions

Paths created in each condition by a representative participant are depicted in Figure 3. To determine whether participants created different path configurations from A-to-B in each condition and whether path configurations in this portion of the path consisted of more mats and were more variable when paths terminated at B than when they continued on to C, we compared the values of each measure in each of the three sets with respect to the A-to-B portion of the paths in the ‘Stop-at-B’ and ‘Continue-to-C’ conditions using paired samples t-tests (see Figure 4). Given the relatively small number of mats used in each condition (Range: 2–8 in ‘Stop-at-B; Range: 2–6 in Continue-to-C), we also compared the number of mats used in each condition using a Wilcoxon signed-rank test. All data analyses were performed in JASP [JASP Team (2025)], version 0.19.3 (jasp-stats.org).

Figure 3.

Paths created by a representative participant in the Stop-at-B condition (left) and the Continue-to-C condition (right).

Figure 4.

Comparison of the configurations of the A-to-B portions of the paths in the Stop-at-B Condition and the Continue-to-C Condition with respect to variables related to Gap Distance (top), Path Trajectory (middle), and Path Variability (bottom). Both mean values and individual data points are depicted. * indicates significant difference at p < .05. Error bars indicate standard error.

Gap Distance

Participants used fewer mats (M_n) in the A-to-B portion of the path in the ‘Continue-to-C’ condition (M = 3.7, SD = 1.0) than in the Stop-at-B condition (M = 4.4, SD = 1.4), t(24) = 2.32, p < .05, Cohen’s d = 0.46 (a difference that was confirmed by the Wilcoxon signed-rank test; W = 121.00, z = 2.11, p < .05; see Figure 4, top left). Participants also placed those mats farther apart (D) in the ‘Continue-to-C’ condition (M = 79.8cm, SD = 16.2) than in the Stop-at-B condition (M = 72.1cm, SD = 20.1), t(24) = 2.11, p < .05, Cohen’s d = 0.42 (a difference that was confirmed by the Wilcoxon signed-rank test; W = 74.00, z = 2.17, p < .05; see Figure 4, top left). However, the difference in Challenge_Perceived values across conditions did not reach significance, t(24) = 1.88, p = .07, Cohen’s d = 0.37; nor did the difference in Challenge_Actual values across conditions, t(24) = 1.99, p = .06, Cohen’s d = 0. 40 (see Figure 4, top).

Path Trajectory

The difference in mean α in the A-to-B portion of the path across conditions was not significant, t(24) = 0.57, p = .57, Cohen’s d = 0.11; nor was the difference in W_max across conditions, t(24) = 1.17, p = .26, Cohen’s d = 0.23; nor was the difference in L_total across conditions, t(24) = 0.16, p = .88, Cohen’s d = 0.03 (see Figure 4, middle). ⁵

Path Variability

The difference in ΔD in the A-to-B portion of the path across conditions was not significant, t(24) = 0.66, p = .52, Cohen’s d = 0.13. However, Δα was smaller in the Continue-to-C condition (M = 18.72°, SD = 22.62°) than in the Stop-at-B condition (M = 33.12°, SD = 38.51°), t(24) = 2.09, p < .05, Cohen’s d = 0.42; see Figure 4, bottom right).

Comparison of A-to-B and B-to-C Portions Paths Within the Continue-to-C Condition

To determine whether participants created different path configurations from A-to-B and from B-to-C when paths continued to C, we compared the values of each measure in each of the three sets of variables with respect to the A-to-B and B-to-C portions of the paths in the ‘Continue-to-C’ conditions using paired samples t-tests. Given the relatively small number of mats used in each portion of the path (Range: 2–6 in A-to-B; Range: 2–5 in B-to-C), we also compared the number of mats used in each condition using a Wilcoxon signed-rank test. There were no significant differences across any of the measures in any of the sets of variables (gap distance, path trajectory, or path variability; see below for details of analyses).

Gap Distance

The difference in M_n across A-to-B and B-to-C portions of the path was not significant, t(24) = 1.50, p = .15, Cohen’s d = 0.30, W = 149.00, z = 0.36, p = .73; nor was the difference in D, t(24) = 0.63, p = .53, Cohen’s d = 0.13]; nor was the difference in Challenge_Perceived, t(24) = 0.64, p = .53, Cohen’s d = 0.13; nor was the difference in Challenge_Actual, t(24) = 0.75, p = .46, Cohen’s d = 0.15 (see Figure 5, top).

Figure 5.

Comparison of the configurations of the A-to-B and B-to-C portions of the paths in the Continue-to-C Condition with respect to variables related to gap distance (top), path trajectory (middle), and path variability (bottom). Both mean values and individual data points are depicted. Error bars indicate standard error.

Path Trajectory

The difference in α across portions of the path was not significant, t(24) = 0.32, p = .75, Cohen’s d = −0.06]; nor was the difference in W_max, t(24) = 0.24, p = .82, Cohen’s d = 0.50]; nor was the difference in L_total, t(24) = 0.85, p = .40, Cohen’s d = 0.17 (see Figure 5, middle). ⁶

Path Variability

The difference in ΔD across A-to-B and B-to-C portions of the path was not significant, t(24) = 0.10, p = .93, Cohen’s d = 0.02; nor was the difference in Δα, t(24) = 0.836, p = .41, Cohen’s d = 0.17 (see Figure 5, bottom).

General Discussion

Previous studies have shown that affordances are perceived ‘as such’ or as ‘complex particulars’—as emergent higher-order relations in a dynamically unfolding set of circumstances rather than merely as combinations of perceived lower-order constituent properties (Higuchi et al., 2011; Mark, 1987; see Turvey, 2015). Moreover, such studies have shown that this is the case even when the lower-order constituent properties of the perceived affordance included other (lower-order) affordances (Thomas & Riley, 2014; Thomas et al., 2018; Wagman & Stoffregen, 2020). We asked whether affordances might be created in the same way. That is, we investigated whether affordances would be created as ‘as such’ or as a ‘complex particular’, rather than merely an as a combination of lower-order affordances.

We investigated this hypothesis in a task in which participants were asked to create a steppingstone path from A-to-B in two conditions—when the path terminated at location B and when the path continued from location B to location C (see Figure 1). We expected that, in each condition, the entire path—from A-to-B when the path terminated at B, and from A-to-B-to-C when the path continued to C—would be created as such (cf. Jansen & Fajen, 2024; see below). That is, we made the novel prediction that affordances for crossing a path from A-to-B are created distinctly from those for crossing a path from A-to-B-to-C.

This expectation generated a pair of specific hypotheses. The first hypothesis was that participants would create different path configurations from A-to-B when the path terminates at B and when the path continues to C. In particular, given that the task constraints of configuring the A-to-B portion of the path emphasize expediency to a greater degree when the path continues to C than when it terminates at B, we expected that participants would configure the A-to-B portion of the path with fewer mats and with less variability in mat placement in the former case than in the latter (cf. Wagman et al., 2024). This expectation also generated the corollary hypothesis that there would be no such differences in path configuration from A-to-B and from B-to-C when the path continued to C. The results supported both specific hypotheses.

As expected, paths from A-to-B comprised more mats and exhibited greater variability in the angular distance between mats when those paths terminated at B than when they continued to C. Accordingly, paths from A-to-B also consisted of shorter distances between mats when those paths terminated at B than when they continued to C (see Figures 3–5). These differences emerged despite the relatively narrow width of the hallway (i.e., 220 cm) relative to the distance between Mat A and Mat B (i.e., 315 cm) and between Mat A and Mat C (i.e., 630 cm), which may have constrained path configuration (in particular, path variability) at least to some degree. Conversely, we did not find any evidence that people configured the A-to-B portion of the path any differently than they did the B-to-C portion of the path when those paths continued to C.

There are biomechanical differences between crossing a path from A-to-B when the path terminates at B and when the path continues to C. For example, the biomechanics of stopping on a target differ from those of merely stepping on a target (Hof, 2008). Therefore, it might be argued that it is not appropriate to compare the configurations of the A-to-B portions of the paths in each case. However, we would argue that such biomechanical differences are constituent of the different higher-order affordances that exist for crossing from A-to-B and from A-to-B-to-C. Therefore, such biomechanical differences serve to justify—rather than invalidate—the comparison of the configurations of the A-to-B portions of the paths in each case. Moreover, while it is the case that stopping on a target requires a longer step length than merely stepping onto the target (Hof, 2008), we found that participants chose to place mats closer together when the path terminated at B than when it continued to C. Therefore, we claim that our results arose from differences in the higher-order affordances of the tasks and not (merely) from biomechanical differences between the tasks.

Together—and only together—the findings that (a) participants would create different path configurations from A-to-B when the path terminates at B and when the path continues to C (see Figure 4) and (b) there were no such differences in path configuration from A-to-B and from B-to-C when the path continued to C (see Figure 5) provide support for the novel hypothesis that the affordances for crossing a path from A-to-B are created distinctly from those for crossing a path from A-to-B-to-C. This pattern of results also provides preliminary support for the more general hypothesis that affordances are both perceived and created ‘as such’—that is, as emergent higher-order relationships rather than as a combination of lower-order constituents of that affordance.

Lower-and Higher-Order Affordances of Steppingstone Paths

By definition, a steppingstone path consists of multiple individual components. Considered in isolation, each of these individual components affords a particular set of behaviors. Each of the mats used in the experiment reported here could be held, carried, placed down, picked up, stood on, stepped from, stepped onto, and so on. To the extent that the affordances of each mat existed independently of each other (and of any path they might be used to create), they could be considered ‘lower-order’ affordances. The affordances of a steppingstone path, however, depend on a particular emergent relation among these ‘lower-order’ affordances in a dynamically unfolding set of circumstances At a minimum, creating a path with the mats used in the experiment reported here meant that each mat had to be placed in such a way that the (lower-order) affordances of stepping from one mat were in particular relation to the (lower-order) affordances for stepping to the next mat.

To the extent that the affordances of a path depend on (and, in fact, emerge from) relations among lower-order affordances of the components of that path, the affordances of the path itself is a ‘higher-order’ affordance (Stoffregen & Wagman, 2025). However, relations between lower and higher affordances is relative. Whereas the affordances of a given path (say from A-to-B) are higher order when considered in relation to the lower-order affordances of the components of that path (i.e., the individual mats), the affordances of that path may be lower order when considered in relation to a larger path (say, from A-to-B-to-C; see Figure 3). Investigating whether the obtained pattern of results would continue occur with continued embeddings of paths into progressively higher-order relations among affordances of paths (e.g., from A-to-B-to-C-to-D, and so on) is an important topic for future research.

The results of the experiment are consistent with those of previous research showing that people can exploit lower-order affordances of individual mats in bringing higher-order affordances of a created paths into existence (Jeschke et al., 2020; Wagman et al., 2024). However, the results of the experiment reported here go beyond those of such previous research by showing that people likewise exploit the lower-order affordances of a given (shorter) path in bringing higher-order affordances of another (longer) path into existence. Moreover, the results also show that the act of bringing emergent higher-order affordances of longer paths into existence influenced both how participants chose to exploit lower-order affordances of individual mats and how they chose to create lower-order affordances of shorter paths (see Figure 4; Peker, et al., 2023; Wagman et al., 2024).

While the experiment reported here builds upon the research by Jeschke et al. (2020) and Wagman et al. (2024), it qualitatively differs from these studies in that we investigated the extent to which upcoming constraints (i.e., the path from B-to-C) influences choices with respect to current path configuration (i.e., the path from A-to-B). Accordingly, the results of the experiment reported here are perhaps more comparable to those reported by Jansen and Fajen (2024) in a virtual drone piloting task. These researchers asked participants to fly a virtual drone through a series of irregularly placed gates in a virtual environment. The results showed that flight path through a given gate (‘gate N’) was influenced by the location of the subsequent gate (‘gate N+1’). Although they did not interpret their results in terms of higher-order affordances, their results suggest that affordances of (virtually) flying a drone through an individual gate are created and exploited distinctly from those for doing so through a sequence of gates. In other words, their results are also consistent with the hypothesis that affordances are perceived and created ‘as such’—as emergent higher-order relationships rather than as a combination of lower-order constituents of that affordance.

Implications for the Design of Steppingstone Paths

In the experiment reported here, path configurations consisted of more mats and were more variable (in terms of angular distance between mats) when the paths terminated at B than when they continued to C. In previous work, one or both such differences in path configuration emerged when participants created paths that emphasized leisure over expedience. In Wagman et al. (2024), for example, participants used more mats to create a path that could be crossed comfortably than one that could be crossed quickly. Similarly, participants used more mats and placed those mats with much greater variability (in terms of angular distance between mats)—often creating longer paths with more changes in direction—when creating a path that would be fun to cross than one that would be easy to cross (see Wagman et al., 2024, Figure 5). ⁷

The results of the present study are consistent with those findings and with the hypothesis that participants created paths from A-to-B that emphasized expedience to a greater degree when the path continued to C than when it terminated at B. In other words, our results are consistent with the hypothesis that participants created more direct paths to a given location when such paths continued through that location on the way to a more distant final destination (i.e., when arriving at the initial location was merely the means to the end) than when such paths terminated at that location (i.e., when arriving at that location was the end to be achieved).

The results showed not only that (a) participants created different path configurations from A-to-B when the path terminated at B and when the path continued to C (see Figure 4) but also that (b) there were no such differences in path configuration from A-to-B and from B-to-C when the path continued to C (see Figure 5). That is, path configuration differed for the same portion of different paths (which were created for different ends) but not for different portions of the same path (which were created for the same end). This suggests to us that observed differences in the A-to-B portion of the paths across conditions reflects the differences in higher-order affordances for traversing each path and not merely noise or error variance. Providing further support for this hypothesis an important topic for future research. For example, such future research could manipulate whether there is an additional task to be performed when reaching a particular location along a given path or the number paths to be traversed as the means to achieve a given end.

Conclusion

Overall, the results are consistent with the hypothesis that the affordances for traversing a surface from A-to-B were both perceived and created distinctly from those for traversing a surface from A-to-B-to-C. Our results are consistent with the proposal that affordances were perceived and created ‘as such’—that is, as emergent higher-order relations rather than as a combination of lower-order constituents of that affordance.

Supplemental Material

sj-csv-1-qjp-10.1177_17470218251395637 – Supplemental material for Is This Your Final Destination? Created Steppingstone Paths Differ Depending on Whether Paths Terminate or Continue

Supplemental material, sj-csv-1-qjp-10.1177_17470218251395637 for Is This Your Final Destination? Created Steppingstone Paths Differ Depending on Whether Paths Terminate or Continue by Jeffrey B. Wagman, Will Ervin, Maisha Tahsin Orthy, Arghya Kashyap and Thomas A. Stoffregen in Quarterly Journal of Experimental Psychology

Supplemental Material

sj-txt-2-qjp-10.1177_17470218251395637 – Supplemental material for Is This Your Final Destination? Created Steppingstone Paths Differ Depending on Whether Paths Terminate or Continue

Supplemental material, sj-txt-2-qjp-10.1177_17470218251395637 for Is This Your Final Destination? Created Steppingstone Paths Differ Depending on Whether Paths Terminate or Continue by Jeffrey B. Wagman, Will Ervin, Maisha Tahsin Orthy, Arghya Kashyap and Thomas A. Stoffregen in Quarterly Journal of Experimental Psychology